1. Field of the Invention
This invention relates to a method and apparatus for controlling a communication network, particularly, but not exclusively, an asynchronous transfer mode (ATM) network.
2. Related Art
ATM networks are controlled to allow statistical multiplexing of calls which enables more calls to be carried than if Synchronous Transfer Mode (STM) methods are used.
Each node or resource in a communication network will have a certain carrying capacity. The capacity comprises an ability for that node to carry a certain number and type of calls. A call comprises a number of connections each connection being a logical end to end link. In order to prevent a node being overloaded it is necessary to control the acceptance of calls by the node and this is achieved by Connection Acceptance Control (CAC) methods.
The revenue generation from any telecommunication network is closely linked to the number of calls allowed onto the network. Therefore, a CAC algorithm needs to be chosen which will maximise the number of calls admitted to the network, whilst maintaining call Quality of Service (QoS), and considering the network resources available. Of additional importance is the speed with which the CAC algorithm makes call acceptance decisions, as this impacts on the subjective customer perception of the service provided.
The QoS of a network or a node of a network depends on various parameters or sets of parameters. The parameters include the probability of the loss of a particular cell of data as it travels through the network, called the cell loss probability (a cell being a time division of the multiplexing scheme containing the packet of data, which is 48 bytes/octets of information and 5 bytes/octets of control information); cell delay which is a measure of the delay a cell experiences as it passes through the network; and cell delay variation which is a measure of the differences in the cell delay times of different cells.
Present CAC methods utilise a procedure called convolution. Convolution based methods are accurate but require considerable computational power and, even then, take a long time causing delays in call set-up on the network which may be unacceptable for certain types of call or services. This problem becomes more and more significant as the mixture of calls becomes more varied. For example, a Broadband Integrated Services Digital Network (BISDN) could carry calls carrying voice data, digital TV data, digital high definition TV data, teleconferencing data, and multimedia data. The data will have different characteristics, for example it could be constant bit rate or variable bit rate and the bandwidth required may also be different, for example, a voice call might require 64 kbps, but a video call might require 140 Mbps. Each node in the network will be able to carry either a certain number of identical connections with the same bandwidth requirements, for example, all voice or, as is more likely, a certain number of different types of calls with different bandwidth requirements, for example, both voice and video.
The rate of a cell stream within a call may also be statistically varying. The statistical variations of the cell stream are often modelled by distributions such as Normal, Guassian, on-off or Bernoulli. A moment generating function of a particular distribution is a way of summarising the behaviour of the distribution in terms of its statistical variation.
In his paper "A Congestion Measure for Call Admission and Traffic Engineering for Multi-Layer Multi-Rate Traffic" (International Journal of Digital and Analog Communication Systems, Volume 3, No. 2, June 1990, UK pp 127-135) Joseph Y. Hui discusses the use of the Chernoff bound to derive a relationship between a quality of service parameter and the traffic carried by a resource in a network. This relationship can be used in a connection admission control method, which is potentially faster than known convolution methods.